Modern Wireless Communication Systems and Networks

Design, Practice, and Implementation

Inbunden, Engelska, 2026

AvBudhaditya Bhattacharyya,Anindita Kundu,Anantha Krishna Chintanpalli,Xavier Fernando

2 799 kr

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This book examines real-world applications, including mobile communication, the Internet of Things (IoT), and wireless sensor networks, emphasizing practical deployment. It further discusses device-to-device communication protocols, wireless personal area networks, and wireless body area networks. The book highlights opportunities and challenges with experimental software-defined radio networks.Features:Provides an in-depth exploration of the recent technologies in the domain of wireless communication systems and networks.Examines real-world applications, including mobile communication, the IoT, and wireless sensor networks and emphasizes practical deployment.Addresses key challenges in 5G wireless networks and beyond, like spectrum management and maximizing utilization while minimizing interference.Discusses mmWave communication, software-defined radio, cognitive radio networks, and non-orthogonal multiple access (NOMA).Explains the concepts of machine learning and deep learning models and how they can be applied in the domain of wireless communication and networks to draw meaningful conclusions.It is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, wireless communications, networking communications, telecommunications, and communications system design.

Produktinformation

Utgivningsdatum2026-08-03
Mått156 x 234 x undefined mm
FormatInbunden
SpråkEngelska
Antal sidor368
FörlagTaylor & Francis Ltd
ISBN9781041112747

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Budhaditya Bhattacharyya is currently working as Professor at School of Electronics Engineering (SENSE), Vellore Institute of Technology (VIT), Vellore. His current research interests include deep learning-based channel estimation strategies for Next Generation wireless networks and intrusion detection analysis for 5G networks.Anindita Kundu is an Associate Professor in the Department of Software Systems, School of Computer Science and Engineering, of Vellore Institute of Technology, Vellore. Her current research interests include Robotic Path Planning, Internet of Things and Opportunistic Networks.Ananthakrishna Chintanpalli is currently a Professor at the Department of Communication Engineering, School of Electronics Engineering, Vellore Institute of Technology (VIT), Vellore. His research interests include signal processing, bio-medical signal processing, auditory modeling to predict speech recognition scores, psychoacoustics, speech processing, and deep neural networks.Xavier Fernando is a Professor at Toronto Metropolitan University (TMU), Canada. His area of research is application of machine learning and artificial intelligence to resolve various engineering and IoT challenges.

Chapter 1. Digital twin-based generative artificial intelligence of things for 6G wireless sensor networks. Chapter 2. Real-Time Workplace Safety Detection using Raspberry PI 5 and Jetson Nano with Computer Vision. Chapter 3. Software Defined Radio (SDR): Experimental Opportunities and Research Challenges. Chapter 4. Improving Efficiency and Innovation in Non-Orthogonal Multiple Access (NOMA) with RIS Techniques and its Future Scope. Chapter 5. Advanced Path Loss Estimation at 5.8 GHz in Heterogeneous Urban Environments Through Hybrid Modelling and Machine Learning. Chapter 6. Energy Management Challenges and Clustering Approaches in Wireless Sensor Networks. Chapter 7. Innovations in Non-Orthogonal Multiple Access with RIS Techniques. Chapter 8. Cradle-Care: Enhancing Baby Safety Using IoT. Chapter 9. Resilient Communication Frameworks: Enhancing Disaster Response with Energy-Efficient MANETs. Chapter 10. UAV-Assisted Wireless Networks: Exploration and Deployment Strategies. Chapter 11. Design and Development of Wireless Personal Area Networks. Chapter 12. Implementation Challenges in Wireless Sensor Networks. Chapter 13. Technical Barriers in Wireless Sensor Networks: Deployment Challenges and Emerging Solutions. Chapter 14. Design and Development of Antennas for Next-Generation Wireless Communication Systems. Chapter 15. A Comparative Analysis of Empirical and Machine Learning Models for LoRa Path Loss Prediction at 915MHz in an NLOS Urban Canyon. Chapter 16. Fuzzy AI-Driven Intelligent Agents for Intrusion Detection in Wireless Sensor Networks: A Cybersecurity Framework Using WSN-DS Dataset. Chapter 17. Distributed Deep Reinforcement Learning Enabled Spectrum and Resource Allocation in 6G Wireless Networks. Chapter 18. Integration of Machine Learning and Deep Learning in Wireless Networks